Twitter API Data Analysis

Introduction: Twitter Data

Twitter is a gold mine of data. Unlike other social platforms, almost every user’s tweets are completely public and pullable. This is a huge plus if you’re trying to get a large amount of data to run analytics on. Twitter data is also pretty specific. Twitter’s API allows to do complex queries like pulling every tweet about a certain topic within the last twenty minutes, or pull a certain user’s non-retweeted tweets.

The main purpose of this task is to take 5 Bangladeshi cricket players official Twitter accounts and get some informations from there. Then analyse these data and do some comparative analysis of their social media accounts.

Importing Libraries

Getting data from API

Data cleaning

For collecting data, I have choosen 5 Bangladeshi Cricket Players official verified Twitter page. The players are:

Then I checked the dataFrame which has 428 rows and 325 columns. I have checked the columns information and choose the columns that has some numerical informations to process further informations. So I create a new data Frame with the necessary columns which has 428 rows and 11 columns.

I also change datatypes as required for the analysis.

Checking missing data

Data Analysis

Analyse the five players frequency of tweets created

Make a new Data frame with numerical data for further analysis

Comparison of players sensitive tweets

Comparison of the user followers account

Comparison of the Retweet counts

Comparison of the user statuses counts

Comparison based on the user favourite counts

Conclusion

It is a very limited data and only a limited analysis has been done. The results I got is in between 8 June 2021 to 16 June 2021. Results I got from these analysis are: